Marine safety and data analytics : vessel crash stop maneuvering performance prediction

Autor: Davide Anguita, Andrea Coraddu, Olena Karpenko, Luca Oneto, Paolo Sanetti, Toine Cleophas, Francesca Cipollini
Jazyk: angličtina
Rok vydání: 2017
Předmět:
Zdroj: Artificial Neural Networks and Machine Learning – ICANN 2017 ISBN: 9783319686110
ICANN (2)
Popis: Crash stop maneuvering performance is one of the key indicators of the vessel safety properties for a shipbuilding company. Many different factors affect these performances, from the vessel design to the environmental conditions, hence it is not trivial to assess them accurately during the preliminary design stages. Several first principal equation methods are available to estimate the crash stop maneuvering performance, but unfortunately, these methods usually are either too costly or not accurate enough. To overcome these limitations, the authors propose a new data-driven method, based on the popular Random Forests learning algorithm, for predicting the crash stopping maneuvering performance. Results on real-world data provided by the DAMEN Shipyards show the effectiveness of the proposal.
Databáze: OpenAIRE
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